Integration Roadmap
Explore our ambitious plans for integrating industry-leading technologies to provide a comprehensive platform for AI/ML and DevOps operations.
Current Integrations
Discover the powerful tools and technologies already integrated into our platform
SonarQube
Code quality and security analysis to identify bugs, vulnerabilities, and code smells in your codebase.
Argo CD
Declarative, GitOps continuous delivery tool for Kubernetes that automates the deployment of applications.
Flux CD
GitOps-based continuous delivery solution for Kubernetes that reconciles cluster state with Git repositories.
Falco
Cloud-native runtime security with real-time threat detection for applications running in cloud environments.
Thanos
Highly available Prometheus setup with long-term storage capabilities for comprehensive monitoring.
Loki
Log aggregation system inspired by Prometheus, optimized for logs from Kubernetes pods.
MinIO
High-performance object storage compatible with Amazon S3 API for cloud-native applications.
Kubeflow
Machine learning toolkit for Kubernetes that simplifies ML workflows with end-to-end orchestration.
Seldon Core
MLOps framework for deploying, managing, and optimizing machine learning models on Kubernetes.
Development Timeline
Our journey of continuous innovation and platform enhancement
Initial DevOps Integrations
completedDeployment of core DevOps tools including SonarQube, Argo CD, and Flux CD to establish continuous delivery pipelines.
Security Framework Implementation
completedIntegration of Falco for runtime security monitoring and threat detection across the platform.
Monitoring Infrastructure
completedDeployment of Thanos and Loki for comprehensive metric and log aggregation and analysis.
Data Storage Solutions
completedImplementation of MinIO object storage for scalable, high-performance data management.
First AI/ML Integrations
completedDeployment of Kubeflow and Seldon Core to enable machine learning workflows and model serving.
Advanced ML Operations
in progressIntegration of KServe and Feast to enhance model serving capabilities and feature management.
ML Lifecycle Management
plannedAddition of MLflow and H2O.ai to provide comprehensive machine learning lifecycle management.
User Experience Enhancement
plannedImplementation of PatternFly and JupyterHub to improve user experience for both developers and data scientists.
Upcoming Integrations
Preview the exciting new integrations coming soon to our platform
KServe
Serverless inferencing on Kubernetes for machine learning models, supporting multiple frameworks.
Feast
Feature store for machine learning that allows teams to manage and serve features to models in production.
MLflow
Machine learning lifecycle platform for experiment tracking, reproducible runs, and model deployment.
H2O.ai
AI and machine learning platform that helps organizations to build and deploy machine learning models.
PatternFly
Enterprise-grade design system for creating consistent and accessible user experiences.
JupyterHub
Multi-user Jupyter notebook environment for data science, machine learning, and analysis.
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